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Show 7 connected to form a surface[18, 11, 6]. Another surface fitting algorithm is opaque cube or cuberille algorithm. In this algorithm cells whose nodes cover the selected threshold values are selected and six polygons, one for each face of the cell, are generated. These polygons are passed to the surface renderer for image generation[16]. The marching cubes algorithm which is a table-based surface fitting procedure takes four data slices into memory and finds the gradients at all of the interior grid-points, marching through all of the interior cells, and fitting small triangles within each cell through which the threshold-value surface passes[26]. The test bed that we are going to use implements this surface fitting algorithm. It will be described in further detail in the next section. 2.3 Image Processing Two-dimensional(2D) signal processing refers to the area of image processing in which the one-dimensional(lD) signal processing techniques of noise filtering, restoration, data compression, and detection have been generalized to two dimensions and thereby made applicable to image data. General image processing[15, 1, 7] consists of operations like image enhancement, image restoration, image detection and estimation, image reconstruction, image data compression, image spectral estimation, and image analysis. We mainly draw upon the image enhancement and interactive image processing literature for feature extraction and feature tracking. One of the image enhancement operation is filtering. Filtering is a generic name for techniques of changing image gray levels to enhance the appearance of objects of interest. Thus a high pass filter, if viewed in the frequency domain, attenuates the low spatial frequencies of an image and enhances the high spatial frequencies. In spatial domain that corresponds to enhancement of small details, edges, and lines. Similarly the low pass filter attenuates the high spatial frequencies of an image and accentuates the low spatial frequencies which corresponds to smoothing the image, suppressing the small details and blurring. Another technique used in image enhancement is the use of edge operators Edge operators detect and measure local discontinuities in the intensity. The result |
